Vehicle corrosion life prediction method, electronic equipment and storage medium
By determining and fitting corrosion parameters in the vehicle corrosion monitoring area, the problems of corrosion parameters accuracy and accounting efficiency in the existing technology in the corrosion monitoring area are solved, and more efficient and accurate vehicle corrosion life prediction is achieved.
Patent Information
- Application Number
- CN202510006048.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-01-02
- Publication Date
- 2025-04-18
AI Technical Summary
The prior art cannot ensure the accuracy of vehicle corrosion parameters and cannot effectively deal with accounting efficiency in diversified corrosion environments.
By determining the first corrosion parameters based on the part properties of each corrosion monitoring area of the vehicle, combining the first fit model and the second fit model, the second and third corrosion parameters are gradually determined, thereby predicting the corrosion strength and regional life, and finally determining the overall corrosion life of the vehicle.
It improves the efficiency and accuracy of obtaining corrosion parameters in a variety of corrosion environments, enhances the accuracy of predicting the anti-corrosion life of the vehicle, and provides support for the anti-corrosion design and quality control of the vehicle.
Smart Images
Figure CN119849186A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of vehicles, and in particular to a vehicle corrosion life prediction method, electronic equipment and storage medium. Background Art
[0002] Corrosion is one of the key factors that lead to damage to vehicle parts. The corrosion of vehicle parts not only reduces their quality and life, but also easily causes safety problems. Therefore, anti-corrosion performance is a key indicator of automobiles.
[0003] When the vehicle is undergoing corrosion resistance testing, various corrosion environments that the vehicle may encounter during actual use will be simulated so that the corrosion resistance of the vehicle in various corrosion environments can be understood. During the corrosion resistance test, the vehicle needs to be subjected to multiple cycle tests. After each cycle test, the corrosion condition of the vehicle is checked. Every time the corrosion condition of the vehicle is checked, the test personnel are required to take pictures of the key corrosion parts of the vehicle, measure and record relevant information (such as corrosion parameters), so as to compare and analyze these relevant information later. Due to the large number of corrosion resistance cycles, the entire corrosion resistance test cycle is long, and the efficiency of obtaining relevant information is low.
[0004] At present, in order to reduce the workload of test personnel, multiple monitoring devices are usually fixed on the vehicle to monitor key components. However, due to the different structures and sizes of the test vehicles, and the need for the vehicle to drive under specified conditions during the test, the stability of the monitoring equipment cannot be ensured, that is, the accuracy of the collected corrosion data cannot be ensured, which in turn affects the accuracy of the vehicle corrosion life prediction using the corrosion data collected by the monitoring equipment.
[0005] In addition, in order to improve the efficiency of obtaining corrosion parameters, the corrosion process is usually accelerated to collect enough data for corrosion calculation in a short time. Although this type of method is more efficient in obtaining corrosion parameters, they are all corrosion parameters in a single corrosion environment. The calculation results based on the corrosion parameters in a single corrosion environment cannot reflect the characteristics of the vehicle in a diversified corrosion environment. Summary of the invention
[0006] The embodiments of the present application disclose a vehicle corrosion life prediction method, electronic device and storage medium. The related technology cannot ensure the accuracy of corrosion parameters and cannot ensure the calculation efficiency in a multi-corrosion environment.
[0007] The present application provides a method for predicting the corrosion life of a vehicle, the method comprising: determining a first corrosion parameter of each corrosion monitoring area of the vehicle based on the part properties corresponding to the area; determining a second corrosion parameter based on the first corrosion parameter and a first fitting model; determining a predicted value of the corrosion intensity of each corrosion monitoring area according to the second corrosion parameter; if the predicted value corresponding to any corrosion monitoring area matches the corresponding actual detection value, obtaining a third corrosion parameter based on the first corrosion parameter and the second fitting model; determining the area life of any corrosion monitoring area based on the first corrosion parameter, the third corrosion parameter and the corrosion prediction model; determining the corrosion life of the vehicle based on the area life of each corrosion monitoring area of the vehicle.
[0008] In some embodiments of the present application, the method also includes: if the regional life of any corrosion monitoring area is within a preset life range, adjusting the manufacturing process of any corrosion monitoring area so that the corresponding carbon emissions of the vehicle are reduced from a first emission value to a second emission value; if the regional life of any corrosion monitoring area exceeds the preset life range, using the first regional material to replace the second regional material of any corrosion monitoring area, and redetermining the regional life of any corrosion monitoring area based on the second regional material.
[0009] In some embodiments of the present application, the method further includes: if the predicted value corresponding to any corrosion monitoring area does not match the corresponding actual detection value, adjusting the collection method of the first corrosion parameter.
[0010] In some embodiments of the present application, determining the first corrosion parameter of each corrosion monitoring area based on the part properties corresponding to each corrosion monitoring area of the vehicle includes: dividing the vehicle into multiple corrosion monitoring areas based on the corrosion microenvironment of the vehicle, each corrosion monitoring area including at least one monitoring point; determining the first corrosion parameter of each monitoring point of each corrosion monitoring area based on the part properties corresponding to the monitoring point of each corrosion monitoring area.
[0011] In some embodiments of the present application, the method also includes: detecting the whole vehicle corrosion rate, the whole vehicle pH and the whole vehicle salt deposition in all corrosion monitoring areas of the vehicle; fitting any two parameters of the whole vehicle corrosion rate, the whole vehicle pH and the whole vehicle salt deposition based on a preset fitting algorithm to determine the first fitting model and the second fitting model, and the first fitting model and the second fitting model have different correlation relationships.
[0012] In some embodiments of the present application, determining the second corrosion parameter based on the first corrosion parameter and the first fitting model includes: if the first fitting model has a correlation between the corrosion rate of the whole vehicle and the pH of the whole vehicle, and the first corrosion parameter includes the pH corresponding to any corrosion monitoring area, then the second corrosion parameter is the corrosion rate corresponding to any corrosion monitoring area; accordingly, obtaining the third corrosion parameter based on the first corrosion parameter and the second fitting model includes: based on the pH corresponding to any corrosion monitoring area and the second fitting model, determining that the third corrosion parameter includes the salt deposition amount corresponding to any corrosion monitoring area, wherein the second fitting model has a correlation between the pH of the whole vehicle and the salt deposition amount of the whole vehicle.
[0013] In some embodiments of the present application, the method further includes: determining the amount of salt deposited on the entire vehicle and the pH value of the entire vehicle based on the electrical conductivity between electrodes; or, performing a dissolution test on preset materials located on multiple corrosion monitoring areas of the vehicle to obtain the amount of salt deposited on the entire vehicle and the pH value of the entire vehicle.
[0014] In some embodiments of the present application, determining whether the predicted value corresponding to the corrosion monitoring area matches the actual detection value corresponding to the corrosion monitoring area includes: obtaining a prediction curve based on the second corrosion parameter and the predicted value; obtaining a detection curve based on the actual detection value; if the prediction curve matches the detection curve, determining that the predicted value matches the actual detection value.
[0015] The present application also provides an electronic device, which includes a processor and a memory, and the processor is used to implement the vehicle corrosion life prediction method when executing a computer program stored in the memory.
[0016] The present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the vehicle corrosion life prediction method is implemented.
[0017] In the vehicle corrosion life prediction method provided in the present application, based on the part attributes corresponding to each corrosion monitoring area of the vehicle, the first corrosion parameter of each corrosion monitoring area is determined, and the most influential corrosion parameter for evaluating each corrosion monitoring area can be obtained through the part attributes. Based on the first corrosion parameter and the first fitting model, the second corrosion parameter is determined; the predicted value of the corrosion intensity of each corrosion monitoring area is determined according to the second corrosion parameter; if the predicted value matches the actual detection value corresponding to any corrosion monitoring area, it means that the first corrosion parameter is accurately collected. When the predicted value matches the actual detection value, the third corrosion parameter is obtained using the second fitting model, so as to determine the corresponding third corrosion parameter of each corrosion monitoring area of the vehicle under a multivariate corrosion environment while reducing the calculation complexity. Based on the first corrosion parameter, the third corrosion parameter and the corrosion prediction model, the regional life of any corrosion monitoring area is determined; based on the regional life of each corrosion monitoring area of the vehicle, the corrosion life of the vehicle is determined. The above method can use the first fitting model and the second fitting model to reduce the difficulty of obtaining the corrosion parameters of each corrosion monitoring area in a diversified corrosion environment, improve the accuracy of predicting the corrosion monitoring area and the vehicle's anti-corrosion life, and the efficiency and accuracy of calculating the corrosion parameters corresponding to the corrosion monitoring area, and can partially replace the corrosion test in the actual vehicle environment, providing strong support for the anti-corrosion design and quality control of the whole vehicle. BRIEF DESCRIPTION OF THE DRAWINGS
[0018] Figure 1 This is a flow chart of a vehicle corrosion life prediction method provided in one embodiment of the present application.
[0019] Figure 2 It is a flowchart for constructing the first fitting model and the second fitting model provided in the embodiment of the present application.
[0020] Figure 3 It is a schematic diagram of the structure of the monitoring device provided in the embodiment of the present application.
[0021] Figure 4 It is a schematic diagram of the installation of the monitoring device provided in the embodiment of the present application.
[0022] Figure 5 It is a schematic diagram of the relationship between the corrosion rate of the whole vehicle and the salt deposition amount of the whole vehicle provided in the embodiment of the present application.
[0023] Figure 6 It is a fitting curve diagram of the whole vehicle corrosion rate and the whole vehicle salt deposition amount provided in the embodiment of the present application.
[0024] Figure 7 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION
[0025] To facilitate understanding, some illustrations of concepts related to the embodiments of the present application are given by way of example for reference.
[0026] It should be noted that in this application, "at least one" means one or more, and "more than one" means two or more than two. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. The terms "first", "second", "third", "fourth", etc. (if any) in the specification, claims and drawings of this application are used to distinguish similar objects, rather than to describe a specific order or sequence.
[0027] In order to solve the technical problem that the relevant technology cannot ensure the accuracy of corrosion parameters and cannot ensure the calculation efficiency in a multi-corrosion environment, the embodiment of the present application provides a vehicle corrosion life prediction method, electronic device and storage medium, which can improve the efficiency of obtaining corrosion parameters and ensure the accuracy of the collected corrosion parameters in a multi-corrosion environment.
[0028] The vehicle corrosion life prediction method provided in the embodiment of the present application can be applied to one or more electronic devices, which may be vehicle-mounted devices, computers, mobile phones, laptops, servers and other devices, wherein the server may be a cloud server or a server cluster. The present application does not limit the type of electronic device.
[0029] like Figure 1 As shown, it is a flow chart of a method for predicting the corrosion life of a vehicle provided by an embodiment of the present application. According to different requirements, the order of each step in the flow chart can be adjusted according to actual requirements, and some steps can be omitted. The method is applied to electronic equipment, such as Figure 7 The electronic device 70 shown. The vehicle corrosion life prediction method comprises the following steps: Step S101, determining a first corrosion parameter of each corrosion monitoring area of the vehicle based on a part property corresponding to the corrosion monitoring area.
[0030] In some embodiments of the present application, in order to perform regional monitoring of the whole vehicle, the whole vehicle can be divided into multiple corrosion monitoring areas according to the corrosion microenvironment category. In one example, it can be divided into nine corrosion monitoring areas, including: the whole vehicle appearance parts outside the vehicle, the ordinary appearance parts outside the vehicle (engine cabin, door, rear cover), the secondary visible appearance parts outside the vehicle, the invisible parts outside the vehicle, the main appearance parts inside the vehicle, the secondary visible parts inside the vehicle, and the invisible parts inside the vehicle. Among them, the corrosion microenvironment refers to the different states of corrosion effects suffered by different areas of the vehicle due to the differences in their specific environmental conditions when they are exposed to the atmospheric environment. It is used to describe the situation in which various parts of the vehicle are subject to corrosion due to differences in the local environment.
[0031] In addition, in order to improve the accuracy of vehicle testing, each corrosion monitoring area is divided into multiple monitoring points according to the properties of the parts. Generally, there is at least one monitoring point on a part, but under the corrosion monitoring area, there may be parts with built structures, which may be affected by environmental factors and accelerate corrosion. Therefore, multiple monitoring points can be set for such parts with built structures.
[0032] In one example, the parts of the structure include but are not limited to steel-aluminum overlap structure parts, which will be accelerated to corrode due to environmental factors such as rain. Therefore, for steel-aluminum overlap structure parts, in addition to setting monitoring points for common electrochemical environmental tests, it is also necessary to set monitoring points for galvanic corrosion tests.
[0033] In some embodiments of the present application, the first corrosion parameter of each corrosion monitoring area may be the same or different. The first corrosion parameter may be determined according to the properties of the part, and the first corrosion parameter may include parameters that affect the corrosion rate, such as temperature, humidity, salt deposition, pH, etc. The above are only examples, and the first corrosion parameter actually monitored is not limited thereto.
[0034] In one example, according to the properties of the secondary visible parts in the vehicle, the liquid film formed by the humidity and temperature in the air can be monitored to obtain the first corrosion parameter. If the vehicle has a liquid film formed by rain / salt spray / car wash water, or a liquid film formed by road water, the secondary visible parts in the vehicle do not need to be monitored.
[0035] Step S102: determining a second corrosion parameter based on the first corrosion parameter and a first fitting model.
[0036] In some embodiments of the present application, the first fitting model may be an algorithm model pre-constructed by a fitting algorithm, which is used to describe the correlation between any two parameters of the vehicle corrosion rate, the vehicle pH, and the vehicle salt deposition. The specific construction method can be referred to as follows Figure 2 The embodiment shown.
[0037] If the first corrosion parameter is the pH value corresponding to any corrosion monitoring area, the first fitting model describing the correlation between the corrosion rate of the whole vehicle and the pH value of the whole vehicle is called to obtain the corrosion rate corresponding to any regional monitoring area when the second corrosion parameter is in an acid environment.
[0038] If the first corrosion parameter is the salt deposition amount corresponding to any corrosion monitoring area, the first fitting model describing the correlation between the corrosion rate of the whole vehicle and the salt deposition amount of the whole vehicle is called to obtain the corrosion rate corresponding to any regional monitoring area in the salt environment, where the second corrosion parameter is.
[0039] If the first corrosion parameter is the corrosion rate corresponding to any corrosion monitoring area in an acid environment, the first fitting model describing the correlation between the corrosion rate of the whole vehicle and the pH of the whole vehicle is called to obtain the second corrosion parameter as the pH corresponding to any regional monitoring area.
[0040] If the first corrosion parameter is the corrosion rate corresponding to any corrosion monitoring area in a salt environment, the first fitting model describing the correlation between the corrosion rate of the whole vehicle and the salt deposition amount of the whole vehicle is called to obtain the second corrosion parameter as the salt deposition amount corresponding to any regional monitoring area.
[0041] If the first corrosion parameter is the pH value corresponding to any corrosion monitoring area, the first fitting model describing the correlation between the salt deposition amount of the whole vehicle and the pH value of the whole vehicle is called to obtain the second corrosion parameter as the salt deposition amount corresponding to any regional monitoring area.
[0042] If the first corrosion parameter is the salt deposition amount corresponding to any corrosion monitoring area, the first fitting model describing the correlation between the salt deposition amount of the whole vehicle and the pH value of the whole vehicle is called to obtain the second corrosion parameter as the pH value corresponding to any regional monitoring area.
[0043] The above is an example, and the specific first fitting model to be called is determined according to the first corrosion parameter, and this application does not limit this. In addition, when the first corrosion parameter includes any two parameters of salt deposition, pH and corrosion rate, the collected data can be mutually verified to be correct.
[0044] In one example, it is known that the amount of salt deposition and the corrosion rate have been collected, and the predicted value of the corrosion rate is calculated using the amount of salt deposition, and it is determined whether the predicted value of the corrosion rate is the same as the collected corrosion rate. If the predicted value of the corrosion rate is the same as the collected corrosion rate, it means that the accurate amount of salt deposition and corrosion rate have been collected, which improves the accuracy of the calculation of the corrosion parameters of the whole vehicle to a certain extent.
[0045] Step S103: determining a predicted value of the corrosion intensity of each corrosion monitoring area according to the second corrosion parameter.
[0046] In some embodiments of the present application, corrosion intensity is used to describe the severity or impact of corrosion, and may include corrosion depth, area, material properties, etc. When the second corrosion parameter is determined, a predicted value of the corrosion intensity of each corrosion monitoring area may be calculated.
[0047] In one example, if the corrosion rate represents the corrosion depth per unit time, the corrosion rate is multiplied by the test time to calculate the corrosion depth, and the corrosion depth is used as the predicted value; if the corrosion rate represents the change in mass per unit time and unit area, the corrosion rate is multiplied by the test time and the coupon area to calculate the mass loss, and the mass loss is used as the predicted value.
[0048] Step S104: if the predicted value corresponding to any corrosion monitoring area matches the corresponding actual detection value, a third corrosion parameter is obtained based on the first corrosion parameter and the second fitting model.
[0049] In some embodiments of the present application, the second fitting model may be an algorithm model pre-constructed by a fitting algorithm, which is used to describe the correlation between any two parameters of the whole vehicle corrosion rate, the whole vehicle pH, and the whole vehicle salt deposition. The specific construction method can be referred to as follows Figure 2 The actual detection value can be obtained by monitoring the device (such as Figure 3 or Figure 4 The corrosion intensity detected by the monitoring device (as shown in the figure) can be a device composed of a hanging plate, a sensor, etc. The test result of the corrosion intensity is related to the test plate. In order to reduce the error, the DC03-FD-B cold-rolled steel plate can be used as the test plate. In addition, the installation position and angle will also affect the detection of corrosion intensity. Generally, the corrosion intensity of cold-rolled steel plates is high on the chassis and roof, among which the side skirts are >80μm / a; the corrosion degree of cold-rolled steel plates at other positions is weaker than that at the installation point of the standard plate, which is the position with the highest corrosion of the whole vehicle (there is no corrosion intensity of the standard plate at other positions). The side skirts and roof positions have different installation angles with the ground, which may cause errors in the test results. The cold-rolled steel plate is parallel to the ground, and the standard plate is perpendicular to the ground. Parallel installation of cold-rolled steel plates is conducive to salt deposition and the degree of corrosion is higher.
[0050] In order to verify whether the predicted value is accurate, the predicted value and the actual detection value can be compared. The comparison method may include: drawing a prediction curve based on the second corrosion parameter and the predicted value. Drawing a detection curve based on the actual detection value. If the prediction curve and the detection curve match, it means that the predicted value and the actual detection value match. If the prediction curve and the detection curve do not match, it means that the predicted value and the actual detection value do not match.
[0051] If the predicted value corresponding to any corrosion monitoring area does not match the corresponding actual detection value, it means that the first corrosion parameter determined during the strengthening test may have an error, then the collection method of the first corrosion parameter can be adjusted, for example, the sensor or hanging piece for collecting the first corrosion parameter can be replaced. In addition, the collected first corrosion parameter can also be replaced, for example, the amount of salt deposition collected is changed to the pH value. The above is just an example, and this application does not limit the collection method of adjusting the first corrosion parameter, which can be set according to actual conditions.
[0052] In some embodiments of the present application, if the predicted value corresponding to any corrosion monitoring area matches the corresponding actual detection value, it means that the collected first corrosion parameter is accurate. When the predicted value matches the actual detection value, calling the second fitting model to obtain the third corrosion parameter can improve the efficiency of obtaining the third corrosion parameter and reduce the complexity of calculating the third corrosion parameter.
[0053] In one example, if the first corrosion parameter is pH, the second fitting model having the correlation between the pH of the whole vehicle and the salt deposition of the whole vehicle is called, so as to obtain the third corrosion parameter as salt deposition. The above is only an example, and the second fitting model having the correlation to be called can be determined according to the first corrosion parameter to determine the third corrosion parameter.
[0054] Step S105, determining the area life of any corrosion monitoring area based on the first corrosion parameter, the third corrosion parameter and the corrosion prediction model.
[0055] In some embodiments of the present application, since the key factors of each corrosion monitoring area are different, the key factors of each corrosion monitoring area can be determined from the first corrosion parameter, the third corrosion parameter and the environmental monitoring parameter. The key factors are input into the corrosion prediction model to obtain the area life corresponding to each corrosion monitoring area. Among them, the corrosion prediction model can be an empirical model, a machine learning model, etc., and the present application does not limit the type of corrosion prediction model.
[0056] In some embodiments of the present application, if the area life of any corrosion monitoring area is within the preset life range, it means that the corrosion monitoring area can meet the corrosion resistance requirements, and the manufacturing process of any corrosion monitoring area can be adjusted so that the carbon emissions corresponding to the vehicle are reduced from the first emission value to the second emission value, thereby achieving the purpose of energy saving and carbon reduction. Among them, the preset life range will vary according to the type of different corrosion monitoring areas, and can be set according to actual conditions, and this application is not limited to this.
[0057] If the regional life of any corrosion monitoring area exceeds the preset life range, the first area material is used to replace the second area material of any corrosion monitoring area. If the vehicle is in the research and development stage, it means that the second area material does not meet the production requirements. If the vehicle is in the use stage, it means that the second area material corrodes quickly, and you can consider replacing the second area material to avoid vehicle damage or safety problems. After replacing the first area material, you can perform the strengthening test again, and re-determine the regional life of any corrosion monitoring area based on the first area material to ensure that the replaced first area material meets the corrosion resistance requirements.
[0058] Step S106, determining the corrosion life of the vehicle based on the area life of each corrosion monitoring area of the vehicle.
[0059] In some embodiments of the present application, after the regional life of each corrosion monitoring area is determined, the vehicle corrosion life can be obtained based on the regional life of each corrosion monitoring area. For example, the regional life of each corrosion monitoring area can be weighted averaged to obtain the vehicle corrosion life.
[0060] In the vehicle corrosion life prediction method provided in the present application, based on the part attributes corresponding to each corrosion monitoring area of the vehicle, the first corrosion parameter of each corrosion monitoring area is determined, and the most influential corrosion parameter for evaluating each corrosion monitoring area can be obtained through the part attributes. Based on the first corrosion parameter and the first fitting model, the second corrosion parameter is determined; the predicted value of the corrosion intensity of each corrosion monitoring area is determined according to the second corrosion parameter; if the predicted value matches the actual detection value corresponding to any corrosion monitoring area, it means that the first corrosion parameter is accurately collected. When the predicted value matches the actual detection value, the third corrosion parameter is obtained using the second fitting model, so as to determine the corresponding third corrosion parameter of each corrosion monitoring area of the vehicle under a multivariate corrosion environment while reducing the calculation complexity. Based on the first corrosion parameter, the third corrosion parameter and the corrosion prediction model, the regional life of any corrosion monitoring area is determined; based on the regional life of each corrosion monitoring area of the vehicle, the corrosion life of the vehicle is determined. The above method uses the first fitting model and the second fitting model to reduce the difficulty of obtaining the corrosion parameters of each corrosion monitoring area in a diversified corrosion environment, improves the accuracy of predicting the corrosion monitoring area and the vehicle's anti-corrosion life, and the efficiency and accuracy of calculating the corrosion parameters corresponding to the corrosion monitoring area. It can also partially replace the corrosion test in the actual vehicle environment, providing strong support for the anti-corrosion design and quality control of the entire vehicle.
[0061] Figure 2 is a flowchart of constructing the first fitting model and the second fitting model provided in the embodiment of the present application, such as Figure 2 As shown in FIG, in order to effectively calculate the corresponding corrosion parameters of each corrosion monitoring area while reducing the computational complexity, this can be achieved by constructing a first fitting model and a second fitting model. The construction process is shown in FIG. Figure 2 As shown, the following steps are included: Step S201, detecting the whole vehicle corrosion rate, the whole vehicle pH value and the whole vehicle salt deposition amount of all corrosion monitoring areas of the vehicle.
[0062] In some embodiments of the present application, a monitoring device may be installed on the vehicle in order to monitor the vehicle. Figure 3The monitoring device hanging piece and sensor are connected to the bracket as shown. Figure 4 As shown in the figure, the hanging piece is fixed to the bracket by fasteners, so that the hanging piece can be removed at any time for corrosion measurement. The sensor can be fixed by adhesion or cable tie. In order to install firmly, the bracket installation hole position, hanging piece and sensor installation position can refer to Figure 4 Schematic diagram shown.
[0063] Among them, the hanging sheet material in the monitoring device can be DC03-FD-B cold-rolled steel plate 50×25×2.0mm, and the hanging sheet size is dynamically adjusted according to the size of the vehicle patch area. The sensor is required to record no less than 32,000 readings (for example, temperature and humidity readings). The dew point temperature can be displayed on the display screen, and the measurement cycle of the sensor includes 2s / 5s / 10s / 30s / 1m / 5m / 10m / 30m / 1h / 2h / 3h / 6h / 12h / 24h. The status indicator of the sensor is displayed by a red / yellow display (LED) and a green LED. The USB interface of the sensor is used to set sensor parameters and corrosion parameter downloads. The sensor can also set an alarm threshold, and when the detected corrosion parameter meets the alarm threshold, an alarm prompt is issued. The relative humidity and temperature collected by the sensor can be displayed using the display screen. The battery life can also be displayed on the display screen. The sensor is used to collect corrosion parameters, including: temperature, humidity, pH, salinity, etc. The temperature and humidity collection time interval may be 1 to 5 minutes, and the collected temperature and humidity are derived every 10 cycles; after the 10th and 20th cycles, the collected pH and salinity are derived, so that subsequent analysis can be performed based on the corrosion parameters collected by the sensor.
[0064] In some embodiments of the present application, after the monitoring device is determined, 1 to 3 detection points are selected in each of the 9 pre-divided corrosion monitoring areas, for a total of 16 detection points, and dynamic environmental parameters and coupon corrosion data of each detection point are collected. The dynamic environmental parameters include temperature and humidity. Coupon corrosion data include the weight of the coupon before the test, the weight of the coupon after the test, corrosion products, salt content, corrosion depth, pH, etc.
[0065] According to the anti-corrosion properties of the vehicle body, 16 test points on the vehicle body are defined as normal environment, water accumulation environment, salt environment and acid environment. In normal environment and water accumulation environment, temperature and humidity are collected; in salt environment, salt deposition is collected; in acid environment, pH is collected.
[0066] The conventional environment is the environment in which the vehicle is in use. In the conventional environment, an interactive sensor is used to collect corrosion parameters, and the collection time interval of the corrosion parameters is 1s-1h. According to actual needs, the collected corrosion parameters can be derived every 1, 10, or 30 cycles, and this application does not limit this.
[0067] The water accumulation environment is an environment with a relative humidity of not less than 80%. In the water accumulation environment, an interactive sensor is used to collect corrosion parameters (temperature and humidity). The collection time interval of the corrosion parameters is 1s-1h. According to actual needs, the collected corrosion parameters can be exported every 1, 10, or 30 cycles, and this application does not limit this.
[0068] The salt environment is an environment with high salt content. During the corrosion test, the salt spray test can be used to simulate the salt environment. In the salt environment, the amount of salt can be collected to calculate the amount of salt deposition. The greater the amount of salt deposition, the greater the corrosion rate of the coupon. The amount of salt deposition can be collected by online transmission (conductivity) or deposition. Among them, the online transmission method is based on the principle of inter-electrode conductivity. During the vehicle test, as the amount of salt deposition increases, the conductivity of the liquid film between the electrodes increases. The conductivity between the electrodes can be measured by a portable conductivity tester. The amount of salt deposition of the vehicle can be calculated based on the inter-electrode conductivity. The deposition measurement uses hygroscopic felt cloth material, which is processed into a uniform area and installed at 16 detection points on the vehicle body. After the vehicle test is completed, the hygroscopic felt cloth material is subjected to a dissolution test, and the amount of salt deposition of the vehicle can be detected by a salinity meter.
[0069] The acid environment is an environment containing acidic substances. During the corrosion test, the acid environment can be simulated by specific chemical reagents or acid mist tests. The higher the corrosion rate, the lower the pH value of the coupon surface. The pH value can be detected by online transmission. During the whole vehicle test, the H+ and OH- generated during the metal corrosion process are detected. The pH value can also be collected by deposition, and the preset materials (for example, hygroscopic felt cloth materials) are processed into a uniform area and installed at 16 detection points on the vehicle body. After the whole vehicle test, the hygroscopic felt cloth material is dissolved to obtain the pH value of the whole vehicle.
[0070] In addition, the monitoring device will also detect the corrosion rate of the entire vehicle while detecting the amount of salt deposition and the pH value of the entire vehicle.
[0071] Step S202, fitting any two parameters of the whole vehicle corrosion rate, the whole vehicle pH and the whole vehicle salt deposition amount based on a preset fitting algorithm to determine the first fitting model and the second fitting model.
[0072] In some embodiments of the present application, after the salt deposition amount, pH value and corrosion rate of the whole vehicle are determined, the least square method can be used to fit the first fitting model and the second fitting model in which any two parameters of the salt deposition amount, pH value and corrosion rate of the whole vehicle have a correlation. In addition, orthogonal least square method, linear interpolation method, Newton interpolation method, Hermit interpolation method, Lagrange interpolation method and cubic spline interpolation method can also be used, and the present application does not limit this.
[0073] Fitting the whole vehicle corrosion rate and the whole vehicle salt deposition is recorded as formula 1, which can be expressed as follows: y1=A1x1 2 +B1x1+C 1; In the formula, y1 represents the corrosion rate of the whole vehicle, x1 represents the salt deposition amount of the whole vehicle, and A1, B1, and C1 are constants.
[0074] Fitting the corrosion rate of the whole vehicle and the pH of the whole vehicle is recorded as formula 2, which is expressed as follows: y2=A2x2 2 +B2x2+C 2; In the formula, y2 represents the corrosion rate of the whole vehicle, x2 represents the pH value of the whole vehicle, and A2, B2, and C2 are constants.
[0075] Fitting the salt deposition amount and pH value of the whole vehicle is recorded as formula 3, which can be expressed as follows: Y3=A3x3 2 +B3x3+C 3; In the formula, y3 represents the pH value of the whole vehicle, x3 represents the salt deposition amount of the whole vehicle, and A3, B3, and C3 are constants.
[0076] Take the fitting of the whole vehicle corrosion rate and the whole vehicle salt deposition as an example, Figure 5 As shown in the figure, the relationship between the recorded vehicle corrosion rate and the vehicle salt deposition is as follows: Figure 6 As shown, this is a curve fitted based on the corrosion rate of the entire vehicle and the salt deposition of the entire vehicle.
[0077] The first fitting model and the second fitting model are Formula 1 or Formula 2 or Formula 3, and the first fitting model is different from the second fitting model. Figure 1 When the salt deposition amount is detected in step S102, Formula 1 is used as the first fitting model to calculate the corrosion rate. Figure 1The step S104 shown uses formula 3 as the second fitting model to calculate the pH value, thereby reducing the complexity of obtaining the pH value and improving the efficiency of the corrosion test. At the same time, in the process of predicting the corrosion life of the vehicle, the corrosion parameters under the diversified corrosion environment are considered, which can improve the accuracy of the whole vehicle corrosion test.
[0078] In an embodiment of the present application, by constructing a first fitting model and a second fitting model for the whole vehicle, the first corrosion parameter corresponding to any corrosion monitoring area collected can be verified through the first fitting model, and the third corrosion parameter can be obtained through the second fitting model to meet the characteristics of the whole vehicle in a diversified corrosion environment, so that the corrosion life of the whole vehicle in the corrosion environment of the whole vehicle can be calculated.
[0079] Figure 7 The electronic device 70 may be a vehicle-mounted device, a computer, a mobile phone, a tablet computer, a notebook computer, a server, etc. The specific type of the electronic device 70 is not limited in any way in the embodiment of the present application.
[0080] exist Figure 7 In the embodiment, the electronic device 70 may include a communication module 710, a memory 720, a processor 730, an input / output (I / O) interface 740 and a bus 750. The processor 730 is coupled to the communication module 710, the memory 720 and the input / output interface 740 through the bus 750.
[0081] The communication module 710 may include a wired communication module and / or a wireless communication module. The wired communication module may provide one or more wired communication solutions such as universal serial bus (USB), controller area network bus (CAN, Controller Area Network). The wireless communication module may provide one or more wireless communication solutions such as wireless fidelity (wireless fidelity, Wi-Fi), Bluetooth (Bluetooth, BT), mobile communication network, frequency modulation (frequency modulation, FM), near field communication technology (near field communication, NFC), infrared technology (infrared, IR), etc.
[0082] The memory 720 may include one or more random access memories (RAM) and one or more non-volatile memories (NVM). The random access memory can be directly read and written by the processor 730, and can be used to store executable programs (such as machine instructions) of other running programs, and can also be used to store user and application data. The random access memory may include static random-access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), etc.
[0083] The non-volatile memory may also store executable programs and user and application data, etc., and may be loaded into the random access memory in advance for direct reading and writing by the processor 730. The non-volatile memory may include a disk storage device and a flash memory.
[0084] The memory 720 is used to store one or more computer programs. The one or more computer programs are configured to be executed by the processor 730. The one or more computer programs include a plurality of instructions, and when the plurality of instructions are executed by the processor 730, the vehicle corrosion detection method executed on the electronic device 70 can be implemented.
[0085] In other embodiments, Figure 7 The electronic device 70 shown also includes an external memory interface for connecting to an external memory to expand the storage capacity of the electronic device 70 .
[0086] The processor 730 may include one or more processing units, for example, the processor 730 may include an application processor (AP), a modem processor, a graphics processor (GPU), an image signal processor (ISP), a controller, a video codec, a digital signal processor (DSP), and / or a neural-network processing unit (NPU), etc. Different processing units may be independent devices or integrated into one or more processors.
[0087] The processor 730 provides computing and control capabilities. For example, the processor 730 is used to execute a computer program stored in the memory 720 to implement the above-mentioned vehicle corrosion detection method.
[0088] The input / output interface 740 is used to provide a channel for user input or output. For example, the input / output interface 740 can be used to connect various input and output devices, such as a mouse, keyboard, touch device, display screen, etc., so that the user can enter information or visualize information.
[0089] The bus 750 is at least used to provide a channel for mutual communication among the communication module 710 , the memory 720 , the processor 730 , and the input / output interface 740 in the electronic device 70 .
[0090] It is to be understood that the structure illustrated in the embodiment of the present application does not constitute a specific limitation on the electronic device 70. In other embodiments of the present application, the electronic device 70 may include more or fewer components than shown in the figure, or combine some components, or split some components, or arrange the components differently. The components shown in the figure may be implemented in hardware, software, or a combination of software and hardware.
[0091] An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. The computer program includes program instructions. The method implemented when the program instructions are executed can refer to the methods in the above-mentioned embodiments of the present application.
[0092] The computer-readable storage medium may be an internal memory of the electronic device described in the above embodiment, such as a hard disk or memory of the electronic device. The computer-readable storage medium may also be an external storage device of the electronic device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device.
[0093] In some embodiments, the computer-readable storage medium may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function, etc.; the data storage area may store data created according to the use of the electronic device, etc.
[0094] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.
[0095] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
[0096] In addition, each functional module in each embodiment of the present application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of hardware plus software functional modules.
[0097] Therefore, no matter from which point of view, the embodiments should be regarded as illustrative and non-restrictive, and the scope of the present application is limited by the appended claims rather than the above description, so it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present application. Any attached figure mark in the claims should not be regarded as limiting the claims involved.
[0098] In addition, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices stated in this application can also be implemented by one unit or device through software or hardware. The words first, second, etc. are used to indicate names, and do not indicate any particular order.
[0099] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present application and are not intended to limit it. Although the present application has been described in detail with reference to the preferred embodiments, a person of ordinary skill in the art should understand that the technical solution of the present application may be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present application.
Claims
1. A method for predicting vehicle corrosion life, characterized in that: The method comprises: Determining a first corrosion parameter of each corrosion monitoring area of the vehicle based on a part property corresponding to the each corrosion monitoring area; Determining a second corrosion parameter based on the first corrosion parameter and the first fitting model; Determine a predicted value of the corrosion intensity of each corrosion monitoring area according to the second corrosion parameter; If the predicted value corresponding to any corrosion monitoring area matches the corresponding actual detection value, a third corrosion parameter is obtained based on the first corrosion parameter and the second fitting model; Determining the regional life of any one of the corrosion monitoring areas based on the first corrosion parameter, the third corrosion parameter and a corrosion prediction model; Based on the area lifetime of each corrosion monitoring area of the vehicle, a lifetime of corrosion of the vehicle is determined.
2. The vehicle corrosion life prediction method according to claim 1, characterized in that: The method further comprises: If the area life of any of the corrosion monitoring areas is within a preset life range, adjusting the manufacturing process of any of the corrosion monitoring areas so that the carbon emissions corresponding to the vehicle are reduced from a first emission value to a second emission value; If the regional life of any corrosion monitoring area exceeds a preset life range, the second regional material of any corrosion monitoring area is replaced with the first regional material, and the regional life of any corrosion monitoring area is re-determined based on the second regional material.
3. The vehicle corrosion life prediction method according to claim 1, characterized in that: The method further comprises: If the predicted value corresponding to any corrosion monitoring area does not match the corresponding actual detection value, the collection method of the first corrosion parameter is adjusted.
4. The vehicle corrosion life prediction method according to claim 1, characterized in that: The determining of the first corrosion parameter of each corrosion monitoring area based on the part attribute corresponding to each corrosion monitoring area of the vehicle includes: Based on the corrosion microenvironment of the vehicle, the vehicle is divided into a plurality of corrosion monitoring areas, each of the corrosion monitoring areas including at least one monitoring point; The first corrosion parameter of each monitoring point in each corrosion monitoring area is determined based on the part properties corresponding to the monitoring points in each corrosion monitoring area.
5. The vehicle corrosion life prediction method according to claim 1, characterized in that: The method further comprises: Detecting the whole vehicle corrosion rate, the whole vehicle pH and the whole vehicle salt deposition in all corrosion monitoring areas of the vehicle; The first fitting model and the second fitting model are determined based on a preset fitting algorithm to fit any two parameters of the whole vehicle corrosion rate, the whole vehicle pH and the whole vehicle salt deposition, and the first fitting model and the second fitting model have different correlation relationships.
6. The vehicle corrosion life prediction method according to claim 5, characterized in that: The determining of the second corrosion parameter based on the first corrosion parameter and the first fitting model includes: If the first fitting model has a correlation relationship between the corrosion rate of the whole vehicle and the pH value of the whole vehicle, and the first corrosion parameter includes the pH value corresponding to any corrosion monitoring area, then the second corrosion parameter is the corrosion rate corresponding to any corrosion monitoring area; Accordingly, obtaining a third corrosion parameter based on the first corrosion parameter and the second fitting model includes: Based on the pH corresponding to any corrosion monitoring area and the second fitting model, the third corrosion parameter is determined to include the salt deposition amount corresponding to any corrosion monitoring area, wherein the second fitting model has a correlation between the pH of the whole vehicle and the salt deposition amount of the whole vehicle.
7. The vehicle corrosion life prediction method according to claim 5, characterized in that: The method further comprises: Determine the salt deposition amount of the whole vehicle and the pH value of the whole vehicle based on the inter-electrode conductivity; or, A dissolution test is performed on preset materials located on multiple corrosion monitoring areas of the vehicle to obtain the salt deposition amount of the entire vehicle and the pH value of the entire vehicle.
8. The vehicle corrosion life prediction method according to claim 1, characterized in that: Determining whether the predicted value corresponding to the corrosion monitoring area matches the actual detected value corresponding to the corrosion monitoring area includes: Based on the second corrosion parameter and the predicted value, obtaining a prediction curve; Based on the actual detection value, a detection curve is obtained; If the prediction curve matches the detection curve, it is determined that the prediction value matches the actual detection value.
9. An electronic device, characterized in that: The electronic device comprises a processor and a memory, wherein the processor is used to execute a computer program stored in the memory to implement the vehicle corrosion life prediction method as claimed in any one of claims 1 to 8.
10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by a processor, the vehicle corrosion life prediction method according to any one of claims 1 to 8 is implemented.